Research interests

Publications

• Taghavi Namin, S, Esmaeilzadeh Fereydani, M, Najafi, M et al 2018, 'Deep phenotyping: Deep learning for temporal phenotype/genotype classification', Plant Methods, vol. 14, no. 66, pp. 1-14pp.
• Hufkens, K, Filippa, G, Cremonese, E et al 2018, 'Assimilating phenology datasets automatically across ICOS ecosystem stations', International Agrophysics, vol. 32, no. 4, pp. 677-687.
• O'Leary, B, Lee, C, Atkin, O et al 2017, 'Variation in Leaf Respiration Rates at Night Correlates with Carbohydrate and Amino Acid Supply', Plant Physiology, vol. 174, no. 4, pp. 2261-2273pp..
• Moore, C, Brown, T, Keenan, T et al 2016, 'Reviews and syntheses: Australian vegetation phenology: New insights from satellite remote sensing and digital repeat photography', Biogeosciences, vol. 13, no. 17, pp. 5085-5102.
• Brown, T, Hultine, K, Steltzer, H et al 2016, 'Using phenocams to monitor our changing earth: Toward a global phenocam network', Frontiers in Ecology and the Environment, vol. 14, no. 2, pp. 84-93.
• Rungrat, T, Awlia, M, Brown, T et al 2016, 'Using Phenomic Analysis of Photosynthetic Function for Abiotic Stress Response Gene Discovery', The Arabidopsis Book, vol. 14, no. e0185, pp. 14pp..
• Nagler, P, Pearlstein, S, Glenn, E et al 2014, 'Rapid dispersal of saltcedar (Tamarix spp.) biocontrol beetles (Diorhabda carinulata) on a desert river detected by phenocams, MODIS imagery and ground observations', Remote Sensing of Environment, vol. 140, pp. 206-219.
• Brown, T, Cheng, R, Sirault, X et al 2014, 'TraitCapture: genomic and environment modelling of plant phenomic data', Current Opinion in Plant Biology, vol. 18, pp. 73-79.
• Brown, T, Cheng, R, Sirault, X et al 2014, 'TraitCapture: genomic and environment modelling of plant phenomic data', Current Opinion in Plant Biology, vol. 18, pp. 73-79.
• Brown, T, Zimmermann, C, Panneton, W et al 2012, 'High-resolution, time-lapse imaging for ecosystem-scale phenotyping in the field', in Jennifer Normanly (ed.), High-Throughput Phenotyping in Plants: Methods and Protocols, Humana Press, New York, pp. 71-96.
• Nagler, P, Brown, T, Hultine, K et al 2012, 'Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western US rivers as determined by multi-scale remote sensing methods', Remote Sensing of Environment, vol. 118, pp. 227-240.

Projects and Grants

Grants information is drawn from ARIES. To add or update Projects or Grants information please contact your College Research Office.

• Australia's Scalable Drone Cloud (Primary Investigator)
• Virtual reality demonstration using 3D point cloud datasets to facilitate a ‘Synth Virtual’ visualisation application (Primary Investigator)